Analysis of seasonal signals and long-term trends in the height time series of IGS sites in China

作     者：MING Feng YANG YuanXi ZENG AnMin JING YiFan 

作者机构：Institute of Geospatial Information Information Engineering University National Key Laboratory of Geo-information Engineering Xi'an Institute of Surveying and Mapping Institute of Navigation and Aerospace Engineering Information Engineering University 

出 版 物：《Science China Earth Sciences》 (中国科学（地球科学英文版）)

年 卷 期：2016年第59卷第6期

页      面：1283-1291页

核心收录：

学科分类：081802[工学-地球探测与信息技术] 08[工学] 0708[理学-地球物理学] 081105[工学-导航、制导与控制] 0818[工学-地质资源与地质工程] 0804[工学-仪器科学与技术] 0704[理学-天文学] 0811[工学-控制科学与工程] 

基　　金：supported by the National High Technology Research and Development Program of China(Grant No.2013AA122501-1) the National Natural Science Foundation of China(Grant Nos.41374019,41020144004,41474015,41274045,41574010) Funded by State Key Laboratory of Geo-information Engineering(Grant No.SKLGIE2015-Z-1-1) 

主　　题：GPS Height time series Seasonal signal Long-term trend STL filter Colored noise 

摘      要：The seasonal signal and long-term trend in the height time series of 10 IGS sites in China are investigated in this paper. The offset detection and outlier removal as well as the removal of common mode error are performed on the raw GPS time-series data developed by the Scripps Orbit and Permanent Array Center(SOPAC). The seasonal-trend decomposition procedure based on LOESS(STL) is utilized to extract precise seasonal signals, followed by an estimation of the long-term trend with the application of maximum likelihood estimation(MLE) to the seasonally adjusted time series. The Up-compo- nents of all sites are featured by obvious seasonal variations, with significant phase and amplitude modulation on some sites. After Kendall s tau test, a significant trend(99% confidence interval) for all sites is achieved. Furthermore, the trends at sites TCMS and TNML have significant changes at epochs 2009.5384 and 2009.1493(95% confidence interval), respectively, using the Breaks For Additive Seasonal and Trend test. Finally, the velocities and their uncertainties for all sites are estimated using MLE with the white noise plus flicker noise model. And the results are analyzed and compared with those announced by SOPAC. The results obtained in this paper have a higher precision than the SOPAC results.